Learner outcome: Forecast the futures of electric vehicle adoption in the United States.

Course: ICT 732 Technology Futures | 3 cr. | Fall 2024

Artifact:

In fall 2024, I took a course called Technology Futures, which focused on applying common forecasting techniques to explore various futures for a technology of my choice. This artifact shares my research and forecast about electric vehicles (EVs), which was designed to provide input into a pseudo-company's strategy development. I followed a framework forecasting process throughout the project, including framing, scanning, forecasting, and visioning. Research and activities in this process included the technology's history, a current state assessment, a stakeholder analysis, trends, plans, key uncertainties, and an expected baseline future. The paper provides detailed information on these components, and the PowerPoint is a summarized format tailored for presenting to a senior company leader.

Work sample: 

Framework Forecasting Project (paper)

Framework Forecasting Project (PowerPoint)

Self-Reflection:

What did you learn?

I learned about Houston’s Foresight Research Framework, a comprehensive and popular method for conducting forecasting projects. Forecasting frameworks use a systematic process to gather data about history, trends, and other information to produce potential futures. Organizations use this systematic process to respond to changes in their environment and inform business strategies. I learned how to complete a forecasting project from start to finish using a common framework.

I also learned how to identify key uncertainties and leading indicators, and how to systematically produce baseline and alternative future scenarios for various technology topics. Additionally, I learned about the factors influencing the adoption of EVs in the United States, including: demographic (individual), situational (technology, financial), contextual (government, infrastructure), and psychological (attitudes, emotions, morals) factors.

Finally, I learned about social change theories and how they relate to technological change. For example, Progress Theory holds that improving the human condition motivates human action, and that significant change will come from human ingenuity, confronting and solving problems, and continuing economic and social development across the world over the long run.

How did you learn this?

I conducted research about electric vehicles and used Houston’s Foresight Research Framework as a guide, breaking the project into the stages of framing, scanning, forecasting, and vision to produce a quality, systematic forecast. The project was driven by the strategic question: “For new vehicle sales, what is the predicted count and percentage that will be electric compared to gas-powered?”

In the framing stage, I defined the purpose, objectives, domain, and scope of the project, which was to forecast the futures of electric vehicle adoption in the U.S. by 2030. I defined date ranges for three time horizons: H1: now to 2026, H2: 2027-2028, and H3: 2029-2030. I researched the current conditions and history of electric vehicles, and identified stakeholders (individuals or organizations that can influence the future of the domain), including the energy sector, automotive industry, consumers, government, and financial institutions. I also performed a STEEP analysis (social, technological, economic, environmental, and political factors) to assess global external factors for long-term strategic planning.

The scanning stage was next and helps to anticipate change and avoid surprises. I researched articles to look for signals of change, documented the type of information (trend, cycle, event), and noted how the future could be different as a result, including potential implications, plausibility, and timeline.

The forecasting stage produced creative, broader, and deeper insights, identifying a wider range of opportunities. Inputs included trends, plans, projections, cycles, and constants for the baseline future, and trend breaks, events (including wildcards), issues, ideas, and key uncertainties for alternative futures.

In the visioning stage, which helps prioritize and make more robust decisions, I envisioned the baseline (expected) future and wrote a hypothetical “day in the life” narrative about EVs, including key assumptions and uncertainties. I also wrote four other narratives about alternative futures.

I also reviewed 10 different social change theories, including Progress Theory, Ideas Theory, and Conflict Theory, comparing and contrasting their stance on questions such as "how do things change?" and "how much control do people have over the future?" I discussed my understanding of these theories and how they have shaped my worldview with classmates.

What were some challenges that you overcame?

One challenge I faced was identifying all stakeholders, understanding their interests, and assessing the importance (low, medium, high) of the EV trajectory on each. I overcame this by first compiling a list, starting with the obvious ones (consumers and the automotive industry), researching key stakeholders online, and then developing a domain map to visualize these items along with the STEEP categories and the project's scope boundaries.

Another challenge was narrowing down all the relevant online information about EV adoption. To overcome this, I looked across a range of sources, paying attention to the stage of media coverage and public awareness. I looked at popular and credible sources like Pew Research and the National Conference of State Legislatures, and purposely looked for five "scanning hits" to identify weak signals, emerging issues, and wild cards (low probability, high impact events).

The final challenge was compiling all the gathered information for the visioning stage to forecast an expected baseline future. I overcame this by reviewing all stages of the framework process I previously completed to ensure I took everything into account, particularly by revisiting the initial strategic question. I forecasted the futures of EV adoption in the US by 2030 by considering all elements: time horizon, current conditions, assumptions, uncertainties, and industry expert predictions, including barriers to adoption and consumer sentiment. I then forecasted alternative futures using a 2x2 planning matrix, which utilized combinations of rapid technological innovation and government support.

How will you apply this information in the future?

I can use the knowledge and hands-on experience gained from applying a forecasting process to strategic decision-making in the workplace. I can use the knowledge about Houston’s Foresight Research Framework to contribute to discussions about strategic plans and major decisions impacting the business. I can accomplish this by mapping out external drivers of change and crafting plausible future scenarios. This systematic process should lead to more informed decision-making to ensure the organization's long-term success. For example, I can help inform decisions about whether a new product line should be launched, a new market should be entered, or if a major IT change should occur.

I can research about a technology in order to forecast futures and compile insights to present to leaders. I am now aware of common forecasting frameworks and have hands-on experience applying them. This includes being able to:

• Use research and forecasting techniques to project technological developments and potential impacts.

• Identify and track leading indicators and key uncertainties that are critical to the company's trajectory.

I will use the forecasting mindset to prepare the organization for change. This involves assessing global external factors through the STEEP analysis and identifying how potential events, trend breaks, and wildcards could affect current business plans. By challenging assumptions and testing proposed strategies against alternative futures, I can help the organization make more robust decisions that are resilient across a range of possible environments.

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